A Pytorch baseline 3D Unet model to segment blood vessels in 3D scans of kidneys. Trained on data from the SenNet + HOA Kaggle competition.
Competition Link: link
Python 3.12.2
> pip install -r requirements.txt
Dataset was obtained from here link. For data access, please accept the organizer's TOS and download.
Dataset was converted to npz format with
> python convert_to_npz.py -h
usage: convert_to_npz.py [-h] [--data_dir DATA_DIR]
Convert data to npz format.
options:
-h, --help show this help message and exit
--data_dir DATA_DIR, -D DATA_DIR
where to load and save data
See notebook for training info. Notebook was run in a Kaggle Environment.
To run locally, configure data in right paths and run train.py.
> python train.py -h
usage: train.py [-h] [--config CONFIG] [--data_dir DATA_DIR]
Train model on 3D kidney.
options:
-h, --help show this help message and exit
--config CONFIG, -C CONFIG
yaml file path for model config
--data_dir DATA_DIR, -D DATA_DIR
where to load and save data